Data Analysis

Analysis of NBA Data for Milwaukee Bucks

Authors

Quinn Campbell

Andrew Johnson

Tristan Costello

Josh Lefkowicz

Hannah Chisholm

Let’s analyze the nba data:

nba<-read_csv("https://cuinnqampbell.github.io/nbamilwaukee.csv")
rmarkdown::paged_table(nba) 

1 Variable Description for nba data.frame

hoopR is an R package for working with men’s basketball data.

The package has functions to access live play by play and box score data from ESPN with shot locations when available. As of version 1.3.0, hoopR is also a full NBA Stats API wrapper with 127 functions added in this release.

It is additionally a scraping and aggregating interface for Ken Pomeroy’s men’s college basketball statistics website, kenpom.com. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.

Variable Descriptions:

type_text: Type of play listed

text: Result of play listed

away_score: Score of away team at time of play

home_score: Score of home team at time of play

period_number: Period in which the play occurred

clock_display_value: Time in period when play occurred

scoring_play: If ‘TRUE,’ play resulted in a score change. If ‘FALSE,’ play did not result in score change

shooting_play: If ‘TRUE,’ play involved a shot. If ‘FALSE,’ play did not involve a shot

season: year of season when play occurred

home_team_name: Name of home team

away_team_name: Name of away team

time: Time at which play occurred

2 Analysis Questions

What is the team free throw percentage for the Milwaukee Bucks on the first free throw during the 2024 season so far?

What is the team free throw percentage for the Milwaukee Bucks on the second free throw during the 2024 season so far?

When favorited at home, how often do the Milwaukee Bucks win that game?

How often do the Milwaukee Bucks call a timeout when they away team scores?

All of these questions will be answered in separate blog posts in the ‘Blog’ section of my website. Thank you for reading! 🏀